diff --git a/monai/networks/blocks/activation.py b/monai/networks/blocks/activation.py
index f6a04e830e..ef2d19b550 100644
--- a/monai/networks/blocks/activation.py
+++ b/monai/networks/blocks/activation.py
@@ -12,6 +12,19 @@
 import torch
 from torch import nn
 
+from monai.utils import optional_import
+
+if optional_import("torch.nn.functional", name="mish")[1]:
+
+    def monai_mish(x):
+        return torch.nn.functional.mish(x, inplace=True)
+
+
+else:
+
+    def monai_mish(x):
+        return x * torch.tanh(torch.nn.functional.softplus(x))
+
 
 class Swish(nn.Module):
     r"""Applies the element-wise function:
@@ -30,6 +43,8 @@ class Swish(nn.Module):
 
     Examples::
 
+        >>> import torch
+        >>> from monai.networks.layers.factories import Act
         >>> m = Act['swish']()
         >>> input = torch.randn(2)
         >>> output = m(input)
@@ -85,6 +100,8 @@ class MemoryEfficientSwish(nn.Module):
 
     Examples::
 
+        >>> import torch
+        >>> from monai.networks.layers.factories import Act
         >>> m = Act['memswish']()
         >>> input = torch.randn(2)
         >>> output = m(input)
@@ -111,10 +128,12 @@ class Mish(nn.Module):
 
     Examples::
 
+        >>> import torch
+        >>> from monai.networks.layers.factories import Act
         >>> m = Act['mish']()
         >>> input = torch.randn(2)
         >>> output = m(input)
     """
 
-    def forward(self, input: torch.Tensor) -> torch.Tensor:
-        return input * torch.tanh(torch.nn.functional.softplus(input))
+    def forward(self, input: torch.Tensor):
+        return monai_mish(input)